Google publishes guide to deploying remote MCP servers on GKE

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Google Cloud has published a developer tutorial showing how to build and deploy a remote Model Context Protocol (MCP) server — a standardized interface that lets AI agents and LLMs access external tools and data sources — on Google Kubernetes Engine (GKE) in roughly 30 minutes. The guide covers using GKE Autopilot for horizontal scaling, the Streamable HTTP transport (MCP's recommended remote-access mode, replacing the older local-only stdio transport), securing the endpoint with the Kubernetes Gateway API and Google-managed SSL certificates, and building the server with FastMCP, a Python framework for MCP. Key benefits highlighted include centralized access for teams and pipelines, stateless scalability for variable agent traffic, and encrypted connections to prevent unauthorized access.